Method of generating an encoded output signal using a manifold association processor having a plurality of pairs of processing elements trained to store a plurality of reciprocal signal pairs
First Claim
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1. A method for generating an encoded output signal from an input signal having a structure comprising a plurality of discrete signal units, the method comprising:
- inputting the input signal into a computer processor having software stored therein for executing a plurality of processing elements, wherein each processing element comprises a logic manifold association processor having an input and an output, and wherein each processing element generates a single output signal;
forming a recursive loop between a pair of processing elements, wherein the output of each pair of processing elements is fed back into the input of the other processing element, and wherein at least one of the pair of processing elements further receives an element input comprising a small subset of the plurality of discrete signal units of the input signal;
training a plurality of pairs of processing elements to store a plurality of reciprocal signal pairs, wherein when a first signal of a reciprocal signal pair of the plurality is input into a first processing element, the first processing element outputs a second signal of the reciprocal signal pair, and when the second signal of the reciprocal signal pair is input into a second processing element, the second processing element outputs the first signal, so that the reciprocal signal pair is locked within the pair of processing elements;
wherein when the at least one of the pair of processing elements that receives the small subset of discrete signal units receives the input signal units, it forces the two processing elements to generate an encoded output associated with the subset of input signal units.
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Abstract
A processor architecture for a learning machine is presented which uses a massive array of processing elements having local, recurrent connections to form global associations between functions defined on manifolds. Associations between these functions provide the basis for learning cause-and-effect relationships involving vision, audition, tactile sensation and kinetic motion. Two arbitrary images hold each other in place in a manifold association processor and form the basis of short-term memory.
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Citations
33 Claims
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1. A method for generating an encoded output signal from an input signal having a structure comprising a plurality of discrete signal units, the method comprising:
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inputting the input signal into a computer processor having software stored therein for executing a plurality of processing elements, wherein each processing element comprises a logic manifold association processor having an input and an output, and wherein each processing element generates a single output signal; forming a recursive loop between a pair of processing elements, wherein the output of each pair of processing elements is fed back into the input of the other processing element, and wherein at least one of the pair of processing elements further receives an element input comprising a small subset of the plurality of discrete signal units of the input signal; training a plurality of pairs of processing elements to store a plurality of reciprocal signal pairs, wherein when a first signal of a reciprocal signal pair of the plurality is input into a first processing element, the first processing element outputs a second signal of the reciprocal signal pair, and when the second signal of the reciprocal signal pair is input into a second processing element, the second processing element outputs the first signal, so that the reciprocal signal pair is locked within the pair of processing elements; wherein when the at least one of the pair of processing elements that receives the small subset of discrete signal units receives the input signal units, it forces the two processing elements to generate an encoded output associated with the subset of input signal units. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A method for extracting knowledge from an input signal having a structure comprising a plurality of discrete signal units, the method comprising:
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transforming the input signal to a higher-dimensional space using a spectral transform to generate an input spectral representation; using an array of processing elements executed by a computer processor, multiplying values of the input spectral representation to produce an associated value, wherein each processing element of the array comprises a different function; mapping the associated value of each processing element by a nonlinear transfer function to generate a processing element output; constructing an estimate of an output spectral representation from the array of mapped processing element outputs; applying a linear transform defined by a reproducing kernel to produce an output signal comprising knowledge extracted from the input signal; and displaying the output signal at an output device. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24, 25, 26, 27)
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28. A system for encoding or decoding an input signal, the input signal having a signal structure, the system comprising:
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a computer having stored therein software for executing a plurality of manifold association processors and for receiving the input signal, wherein each manifold association processor comprises; a processor input and a processor output and wherein each processor generates a single output signal; a recursive loop between a pair of processors, wherein the output of each pair of processors is fed back into the input of the other processor, and wherein at least one of the pair of processors further receives an element input comprising a small subset of discrete signal units of the input signal, wherein the processors are trained to store a plurality of reciprocal signal pairs, wherein when a first signal of a reciprocal signal pair of the plurality is input into a first processing element, the first processing element outputs a second signal of the reciprocal signal pair, and when the second signal of the reciprocal signal pair is input into a second processing element, the second processing element outputs the first signal, so that the reciprocal signal pair is locked within the pair of processing elements, wherein when the at least one of the pair of processing elements that receives the small subset of discrete signal units receives the input signal units, it forces the two processing elements to generate an encoded output associated with the subset of input signal units; and means for combining the processor outputs of all the individual processors to form the encoded output signal corresponding to the input signal. - View Dependent Claims (29, 30, 31, 32, 33)
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Specification